Aims

Studies of infant hip development to date have been limited by considering only the changes in appearance of a single ultrasound slice (Graf’s standard plane). We used 3D ultrasound (3DUS) to establish maturation curves of normal infant hip development, quantifying variation by age, sex, side, and anteroposterior location in the hip.

Spine and torso models were generated concurrently with x-rays for twenty-three patients undergoing scoliosis brace treatment. Clinical indices of spinal deformity and torso surface asymmetry indices were computed from models obtained when patient was first recruited and at approximately one year’s follow-up. Significant correction changes of the torso shape were detected in indices including orientation of cross-sectional principal axes of inertia (p=0.048) and Back Surface Rotation (p=0.08) though spinal corrections were from not significant to subtle (0.20_p_0.88). Trunk asymmetry should be assessed for an objective evaluation and understanding of the effect produced by a specific treatment.

To assess changes in torso geometry and spinal deformity during treatment of idiopathic scoliosis with rigid brace.

Relationship between torso surface geometry and spinal deformity when a rigid brace is applied is essential for better understanding of brace treatment mechanism and optimal application of external forces.

Three-dimensional torso surface models were generated concurrently with postero-anterior x-rays for twenty-three patients undergoing scoliosis brace treatment, when first recruited and at approximately one year’s follow-up. Torso asymmetry indices describing principal axis orientation, back surface rotation, and asymmetry of the centroid line, left and right half-areas and the spinous process line were computed. The statistical paired t-Test (95% CI) was performed to test the probability that no difference exist after one year of treatment in both spinal and torso asymmetry indices.

After one year follow-up patients showed a mean increase of only 2° for the major Cobb angle. This was consistent with not significant to subtle corrections found in clinical (p=0.88) and computed (p=0.75) Cobb angle, lateral deviation (p=0.20), orientation of plane of maximum deformity (p= 0.58) and maximum vertebral axial rotation (p=0.83). Furthermore, significant correction changes of the torso shape were detected in the orientation of cross-sectional principal axes (PAX) of inertia (p=0.048) and Back Surface Rotation (p=0.08).

Here we have shown that we can acquire 3D torso surface and reliably measured a set of indices of transverse torso asymmetry. Future work will look at indication of predictive potential of torso surface indices.

Funding: AHFMR, CIHR, Fraternal Order of Eagles, NSERC, GEOIDE.

Recent studies have shown that scoliotic deformity can be estimated accurately from deformity of the full three hundred and sixty degrees torso shape. However, acquisition of these data requires an expensive multi-scanner system. If it was possible to estimate accurately scoliosis from the back surface shape alone, a single scanner and simplified analysis methods could be used. Here, we estimated the Cobb angle within ten degrees in 84% of forty-six patients from back surface data, compared to 99% within ten degrees for a previous, larger study using the entire torso shape. These results suggested that both back-surface and full-torso models for Cobb angle estimation should be pursued for their potential merits.

The surface deformity of scoliosis, often the primary patient complaint, progresses non-linearly with the underlying spinal deformity. If it was possible to estimate reliably the degree of scoliosis from the surface, adolescent patients with non-progressing scoliosis could be spared harmful X-ray radiation. Some of us have previously estimated the scoliotic Cobb angle from three hundred and sixty degrees torso surface deformity. Here, we tested how accurately the Cobb angle could be estimated from back surface data alone, which are easier and less expensive to obtain than full-torso data.

A genetic algorithm selected the clinical parameters to be used by a neural network to estimate scoliosis deformity from back surface deformity. We had forty-six consecutive patients with right-thoracic curves (Cobb angles eleven to ninety-seven degrees), in whom fifteen indices were available including age, height, bracing status, scoliometer reading, back surface rotation, and cosmetic score of landmark asymmetry. Those data were used by a neural network to estimate the Cobb angle within ten degrees in 84% of patients, a 30% improvement over regression-model accuracy, though less accurate than use of the three hundred and sixty degrees torso shape which estimated up to 99% of curves within ten degrees in a previous study.

Neural network predictive accuracy was better when using the full three hundred and sixty degrees torso shape, but the simpler and more economical acquisition of back surface data alone also gave promising results. This pilot comparison study suggested that both models (using back surface data alone vs. using three hundred and sixty degrees torso data) should continue to be developed in attempts to optimize surface estimation of scoliosis.